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Purpose <p>We used data from the IPF-PRO Registry of patients with idiopathic pulmonary fibrosis (IPF) to identify characteristics that predicted survival for a further &gt; 5&#xa0;years.</p> Methods <p>Participants had IPF that was diagnosed or confirmed at the enrolling center in the previous 6&#xa0;months. Patients were followed prospectively. A Classification And Regression Tree (CART) was used to identify predictors of survival &gt; 5 versus ≤ 5&#xa0;years following enrollment. The following variables, assessed at enrollment, were considered: age; body mass index (BMI); former smoker; current smoker; time from first imaging evidence, symptoms, or diagnosis of IPF to enrollment; forced vital capacity (FVC) % predicted; diffusing capacity of the lungs for carbon monoxide (DLco) % predicted; antifibrotic drug use; supplemental oxygen use; history of cardiac disease; pulmonary hypertension; COPD/emphysema; and rural location.</p> Results <p>The analysis cohort comprised 819 patients, of whom 278 (33.9%) survived &gt; 5&#xa0;years. DLco % predicted, supplemental oxygen use and FVC % predicted were the most important variables for predicting survival &gt; 5 versus ≤ 5&#xa0;years after enrollment. The importance of these variables (scaled such that the most important had an importance of 100%) was 100%, 78.2% and 74.2%, respectively. The optimism-corrected area under the curve (AUC) of the CART was 0.72, with an accuracy of 0.72.</p> Conclusion <p>Among patients enrolled in the IPF-PRO Registry, a decision tree that included DLco % predicted, oxygen use and FVC % predicted facilitated the prediction of survival &gt; 5&#xa0;years. Understanding predictors of longer-term survival may facilitate conversations with patients about their prognosis and treatment.</p>

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Predictors of Long-Term Survival in Patients with Idiopathic Pulmonary Fibrosis: Data from the IPF-PRO Registry

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年3月9日

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  • Hyun J. Kim,
  • Jeremy M. Weber,
  • Megan L. Neely,
  • Amy Hajari Case,
  • Aiham H. Jbeli,
  • Peide Li,
  • Amy L. Olson,
  • Laurie D. Snyder,
  • Albert Baker,
  • Scott Beegle,
  • John A. Belperio,
  • Rany Condos,
  • Francis Cordova,
  • Brian Southern,
  • Daniel Dilling,
  • John Fitzgerald,
  • Kevin R. Flaherty,
  • Kevin Gibson,
  • Mridu Gulati,
  • Kalpalatha Guntupalli,
  • Nishant Gupta,
  • David Hotchkin,
  • Tristan J. Huie,
  • Robert J. Kaner,
  • Lisa H. Lancaster,
  • Joseph A. Lasky,
  • Doug Lee,
  • Timothy Liesching,
  • Randolph Lipchik,
  • Jason Lobo,
  • Tracy R. Luckhardt,
  • Yolanda Mageto,
  • Marta Kokoszynska,
  • Lake Morrison,
  • Andrew Namen,
  • Justin M. Oldham,
  • Tessy Paul,
  • David Zhang,
  • Mary Porteous,
  • Rishi Raj,
  • Murali Ramaswamy,
  • Tonya Russell,
  • Paul Sachs,
  • Zeenat Safdar,
  • Shirin Shafazand,
  • Ather Siddiqi,
  • Reginald Fowler,
  • Mary E. Strek,
  • Hiram Rivas-Perez,
  • Jeremy Tabak,
  • Rajat Walia,
  • Timothy P. M. Whelan

摘要

Purpose

We used data from the IPF-PRO Registry of patients with idiopathic pulmonary fibrosis (IPF) to identify characteristics that predicted survival for a further > 5 years.

Methods

Participants had IPF that was diagnosed or confirmed at the enrolling center in the previous 6 months. Patients were followed prospectively. A Classification And Regression Tree (CART) was used to identify predictors of survival > 5 versus ≤ 5 years following enrollment. The following variables, assessed at enrollment, were considered: age; body mass index (BMI); former smoker; current smoker; time from first imaging evidence, symptoms, or diagnosis of IPF to enrollment; forced vital capacity (FVC) % predicted; diffusing capacity of the lungs for carbon monoxide (DLco) % predicted; antifibrotic drug use; supplemental oxygen use; history of cardiac disease; pulmonary hypertension; COPD/emphysema; and rural location.

Results

The analysis cohort comprised 819 patients, of whom 278 (33.9%) survived > 5 years. DLco % predicted, supplemental oxygen use and FVC % predicted were the most important variables for predicting survival > 5 versus ≤ 5 years after enrollment. The importance of these variables (scaled such that the most important had an importance of 100%) was 100%, 78.2% and 74.2%, respectively. The optimism-corrected area under the curve (AUC) of the CART was 0.72, with an accuracy of 0.72.

Conclusion

Among patients enrolled in the IPF-PRO Registry, a decision tree that included DLco % predicted, oxygen use and FVC % predicted facilitated the prediction of survival > 5 years. Understanding predictors of longer-term survival may facilitate conversations with patients about their prognosis and treatment.